基于MILP-IGA的群塔吊运作业优化调度研究

Modeling and Optimization of Multiple Crane Service SchedulesBased On MILP-IGA

建筑施工现场中频繁的群塔交叉作业存在较高的风险隐患,传统的塔吊防碰撞系统利用紧急制动等方法避免碰撞,但会严重影响运输效率。本研究提出一种主动避让的优化调度方法,通过调整吊运任务执行顺序和选择物料供应位置,避免相邻塔吊同时驶入重叠区域。首先基于混合整数线性规划(Mixed-Integer Linear Programming,MILP)建立物料吊装任务聚类分配模型,实现吊运任务的优化分配。随后引入变量和约束条件建立吊运任务排序模型,并设计改进遗传算法(Improved Genetic Algorithm,IGA)实现快速求解。在工程案例中对比了优化调度方法与信号工调度的任务排序,运输成本减少了20.68%,等待总时间由11.99 min降为0。结果显示该模型与算法能够为实际项目快速提供优化调度方案,在保证塔吊安全运行的前提下节约运输成本。

Frequent cross-operation of multiple crane entails significant dangers.Traditionally,tower crane collision alert system would reduce transportation efficiency by using emergency braking to prevent collisions.This study proposed an active avoidance scheduling method.The method can prevent the possible crane collisions in overlapping work areas by adjusting the sequence of requests and selecting the material storage locations.Based on the Mixed-Integer Linearing Programming(MILP),a clustering model was developed to optimize the request assignment to each tower crane.A model for requests scheduling was developed by introducing variables and constraints.An improved genetic algorithm(IGA)was proposed to efficiently solve the scheduling optimization model.A numerical example was introduced to compare the optimized scheduling solution with the sequence planned on site.It reveals that the model can save overall transportation cost by 20.68%and waiting time from 11.99 to 0 minutes.The results reveal that the optimization model and algorithm can efficiently schedule the requests and guarantee the operation safety with low transportation cost.